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Bayesian adaptive design: the future for regional anesthesia trials?
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Authors

  • Robert Gotmaker Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia Department of Anaesthesia and Acute Pain Medicine, St Vincent’s Hospital, Melbourne, Victoria, Australia PubMed articlesGoogle scholar articles
  • Michael J Barrington Department of Anaesthesia and Acute Pain Medicine, St Vincent’s Hospital, Melbourne, Victoria, Australia Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia PubMed articlesGoogle scholar articles
  • John Reynolds Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia PubMed articlesGoogle scholar articles
  • Lorenzo Trippa Department of Biostatistics, Dana-Farber Cancer Institute and Harvard TH Chan School of Public Health, Boston, Massachusetts, USA PubMed articlesGoogle scholar articles
  • Stephane Heritier Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Stephane Heritier, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Vic, Australia; stephane.heritier{at}monash.edu

Citation

Gotmaker R, Barrington MJ, Reynolds J, et al
Bayesian adaptive design: the future for regional anesthesia trials?
Regional Anesthesia & Pain Medicine 2019;44:617-622.

Publication history

  • Received November 9, 2018
  • Revision received January 13, 2019
  • Accepted January 26, 2019
  • First published March 2, 2019.
Online issue publication 
June 10, 2020

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© American Society of Regional Anesthesia & Pain Medicine 2019. No commercial re-use. See rights and permissions. Published by BMJ.